The response characteristics of TM image to the soil moisture in the Tarim River are the research object. Selected the image spectrum (R), spectrum reciprocal (1/R), the logarithm of reciprocal spectrum lg(1/R) and removal normalized difference vegetation index (R(c)) of four spectral index were selected to establish the soil moisture content prediction model, the variance test was used to validate the model significance, the model accuracy level was divided by the posterior variance examination. The results showed that: the model accuracy of the logarithm of reciprocal spectrum lg(1/R) prediction of soil moisture is the highest, and achieved a good level for the monitoring of soil moisture content (0 - 30 cm). The model accuracy of the spectral (R) and spectral reciprocal (1/R) prediction of soil moisture is lower than logarithm of reciprocal spectrum with only the individual layers (0-30, 0-50 cm, etc.) reaching the qualified level or narrouly qualified level. The model accuracy of the removal normalized difference vegetation index (R(c)) prediction of soil moisture is the lowest. Besides, the best prediction depth of every model is the depth of 0-30 cm, and if the soil depth is too deep or too shallow, the prediction accuracy will decrease.
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Glob Chang Biol
January 2025
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.
Terrestrial vegetation is a key component of the Earth system, regulating the exchange of carbon, water, and energy between land and atmosphere. Vegetation affects soil moisture dynamics by absorbing and transpiring soil water, thus modulating land-atmosphere interactions. Moreover, changes in vegetation structure (e.
View Article and Find Full Text PDFEcol Evol
January 2025
Department of Plant Biology and Ecology, College of Life Science Nankai University Tianjin P. R. China.
In the context of global climate change, exploring how plant adaptation and responses to drought vary among different regions are crucial to understanding and predicting its geographic distribution. In this study, to explore the drought adaptation and responses of the dominant species in the semi-arid Eurasian Steppes and their differences among the different regions in terms of growth, physiology, and RNA-seq transcriptome, was chosen as the study material, and a seed source (three regions: eastern, middle, and western regions) × soil moisture treatment (three treatments: control, light drought, and heavy drought) two-factor experiment was conducted. (1) Four growth traits for individuals from the western region were significantly lower than those from the other two regions.
View Article and Find Full Text PDFZhongguo Xue Xi Chong Bing Fang Zhi Za Zhi
December 2024
Yunnan Institute of Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory for Zoonosis Control and Prevention, Dali, Yunnan 671000, China.
Objective: To predict the potential geographic distribution of in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into surveillance and control in Yunnan Province.
Methods: The snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population).
Nat Commun
January 2025
The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China.
Precipitation is an important factor influencing the date of foliar senescence, which in turn affects carbon uptake of terrestrial ecosystems. However, the temporal patterns of precipitation frequency and its impact on foliar senescence date remain largely unknown. Using both long-term carbon flux data and satellite observations across the Northern Hemisphere, we show that, after excluding impacts from of temperature, radiation and total precipitation by partial correlation analysis, declining precipitation frequency may drive earlier foliar senescence date from 1982 to 2022.
View Article and Find Full Text PDFFront Microbiol
January 2025
College of Grassland Science, Xinjiang Agricultural University, Urumqi, China.
Iron (Fe) minerals possess a huge specific surface area and high adsorption affinity, usually considered as "rust tanks" of organic carbon (OC), playing an important role in global carbon storage. Microorganisms can change the chemical form of Fe by producing Fe-chelating agents such as side chains and form a stable complex with Fe(III), which makes it easier for microorganisms to use. However, in seasonal frozen soil thawing, the succession of soil Fe-cycling microbial communities and their coupling relationship with Fe oxides and Fe-bound organic carbon (Fe-OC) remains unclear.
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